Sentence Similarity
sentence-transformers
PyTorch
gpt_neo
feature-extraction
mteb
Eval Results (legacy)
Instructions to use Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
SGPT-125M-weightedmean-msmarco-specb-bitfit / evaluation /mteb /AmazonCounterfactualClassification.json
Download evaluation/mteb/AmazonCounterfactualClassification.json from Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit: direct link, hf CLI and curl.
- Browser
- Download file 2.9 kB
-
https://huggingface.co/Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit/resolve/c135b3471857e3d8db7fd00ee981d7d1948f0770/evaluation/mteb/AmazonCounterfactualClassification.json
- Command line
-
hf download hf://Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit@c135b3471857e3d8db7fd00ee981d7d1948f0770/evaluation/mteb/AmazonCounterfactualClassification.json
-
curl -L -o AmazonCounterfactualClassification.json https://huggingface.co/Muennighoff/SGPT-125M-weightedmean-msmarco-specb-bitfit/resolve/c135b3471857e3d8db7fd00ee981d7d1948f0770/evaluation/mteb/AmazonCounterfactualClassification.json
2.9 kB
| { | |
| "test": { | |
| "de": { | |
| "accuracy": 0.5688436830835117, | |
| "accuracy_stderr": 0.029093897773991517, | |
| "ap": 0.7267279104379771, | |
| "ap_stderr": 0.010217580709985108, | |
| "f1": 0.5444984024378641, | |
| "f1_stderr": 0.02389292222743725, | |
| "main_score": 0.7267279104379771 | |
| }, | |
| "en": { | |
| "accuracy": 0.6123880597014926, | |
| "accuracy_stderr": 0.031379155023926214, | |
| "ap": 0.25854431650388643, | |
| "ap_stderr": 0.016981404964613887, | |
| "f1": 0.557518627628186, | |
| "f1_stderr": 0.024487163893960967, | |
| "main_score": 0.25854431650388643 | |
| }, | |
| "en-ext": { | |
| "accuracy": 0.5827586206896551, | |
| "accuracy_stderr": 0.048062843086995724, | |
| "ap": 0.14067357642500386, | |
| "ap_stderr": 0.013693676529546861, | |
| "f1": 0.4817231851869133, | |
| "f1_stderr": 0.030208933707168584, | |
| "main_score": 0.14067357642500386 | |
| }, | |
| "evaluation_time": 52.9, | |
| "ja": { | |
| "accuracy": 0.5464668094218414, | |
| "accuracy_stderr": 0.04850756984311426, | |
| "ap": 0.11776694555054965, | |
| "ap_stderr": 0.006424556406403228, | |
| "f1": 0.44526622834078766, | |
| "f1_stderr": 0.029061809459351582, | |
| "main_score": 0.11776694555054965 | |
| } | |
| }, | |
| "validation": { | |
| "de": { | |
| "accuracy": 0.5918454935622317, | |
| "accuracy_stderr": 0.024350314081552426, | |
| "ap": 0.7372017677238578, | |
| "ap_stderr": 0.010683816932118138, | |
| "f1": 0.5642882005866563, | |
| "f1_stderr": 0.02007457192846663, | |
| "main_score": 0.7372017677238578 | |
| }, | |
| "en": { | |
| "accuracy": 0.6113432835820894, | |
| "accuracy_stderr": 0.038501677223608914, | |
| "ap": 0.2227104848944061, | |
| "ap_stderr": 0.01397442904182502, | |
| "f1": 0.5393378654542855, | |
| "f1_stderr": 0.027447873327993155, | |
| "main_score": 0.2227104848944061 | |
| }, | |
| "en-ext": { | |
| "accuracy": 0.5848348348348348, | |
| "accuracy_stderr": 0.043238290090035825, | |
| "ap": 0.13520924912279636, | |
| "ap_stderr": 0.011096096922529254, | |
| "f1": 0.4794399892152111, | |
| "f1_stderr": 0.02584441348504658, | |
| "main_score": 0.13520924912279636 | |
| }, | |
| "evaluation_time": 43.78, | |
| "ja": { | |
| "accuracy": 0.5523605150214592, | |
| "accuracy_stderr": 0.04902106769175921, | |
| "ap": 0.11348392156508444, | |
| "ap_stderr": 0.012428212574320868, | |
| "f1": 0.4441089123442944, | |
| "f1_stderr": 0.03136061225772234, | |
| "main_score": 0.11348392156508444 | |
| } | |
| }, | |
| "dataset_version": null, | |
| "mteb_version": "0.0.2" | |
| } |